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articles/ai-services/computer-vision/computer-vision-how-to-install-containers.md

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ms.service: azure-ai-vision
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ms.topic: how-to
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ms.date: 08/29/2023
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ms.date: 06/26/2024
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ms.author: pafarley
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keywords: on-premises, OCR, Docker, container
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---
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# Install Azure AI Vision 3.2 GA Read OCR container
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Containers enable you to run the Azure AI Vision APIs in your own environment. Containers are great for specific security and data governance requirements. In this article you'll learn how to download, install, and run the Read (OCR) container.
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Containers let you run the Azure AI Vision APIs in your own environment and can help you meet specific security and data governance requirements. In this article you'll learn how to download, install, and run the Azure AI Vision Read (OCR) container.
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The Read container allows you to extract printed and handwritten text from images and documents with support for JPEG, PNG, BMP, PDF, and TIFF file formats. For more information, see the [Read API how-to guide](how-to/call-read-api.md).
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The Read container allows you to extract printed and handwritten text from images and documents in JPEG, PNG, BMP, PDF, and TIFF file formats. For more information on the Read service, see the [Read API how-to guide](how-to/call-read-api.md).
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## What's new
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The `3.2-model-2022-04-30` GA version of the Read container is available with support for [164 languages and other enhancements](./whats-new.md#may-2022). If you're an existing customer, follow the [download instructions](#get-the-container-image) to get started.
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* Choose text line output order from default to a more natural reading order for Latin languages only.
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* Text line classification as handwritten style or not for Latin languages only.
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If you're using Read 2.0 containers today, see the [migration guide](read-container-migration-guide.md) to learn about changes in the new versions.
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If you're using the Read 2.0 container today, see the [migration guide](read-container-migration-guide.md) to learn about changes in the new versions.
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## Prerequisites
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articles/ai-services/computer-vision/includes/how-to-guides/analyze-image-40-js.md

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ms.topic: include
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ms.custom: references_regions
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---
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## Prerequisites

articles/ai-services/computer-vision/includes/how-to-guides/analyze-image-40-python.md

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ms.custom: references_regions
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## Prerequisites

articles/ai-services/computer-vision/overview-ocr.md

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ms.service: azure-ai-vision
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ms.topic: overview
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ms.date: 04/30/2024
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ms.date: 06/26/2024
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ms.author: pafarley
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ms.custom: devx-track-csharp
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OCR or Optical Character Recognition is also referred to as text recognition or text extraction. Machine-learning-based OCR techniques allow you to extract printed or handwritten text from images such as posters, street signs and product labels, as well as from documents like articles, reports, forms, and invoices. The text is typically extracted as words, text lines, and paragraphs or text blocks, enabling access to digital version of the scanned text. This eliminates or significantly reduces the need for manual data entry.
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## How is OCR related to Intelligent Document Processing (IDP)?
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Intelligent Document Processing (IDP) uses OCR as its foundational technology to additionally extract structure, relationships, key-values, entities, and other document-centric insights with an advanced machine-learning based AI service like [Document Intelligence](../../ai-services/document-intelligence/overview.md). Document Intelligence includes a document-optimized version of **Read** as its OCR engine while delegating to other models for higher-end insights. If you are extracting text from scanned and digital documents, use [Document Intelligence Read OCR](../../ai-services/document-intelligence/concept-read.md).
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## OCR engine
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Microsoft's **Read** OCR engine is composed of multiple advanced machine-learning based models supporting [global languages](./language-support.md). It can extract printed and handwritten text including mixed languages and writing styles. **Read** is available as cloud service and on-premises container for deployment flexibility. With the latest preview, it's also available as a synchronous API for single, non-document, image-only scenarios with performance enhancements that make it easier to implement OCR-assisted user experiences.
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Microsoft's **Read** OCR engine is composed of multiple advanced machine-learning based models supporting [global languages](./language-support.md). It can extract printed and handwritten text including mixed languages and writing styles. **Read** is available as cloud service and on-premises container for deployment flexibility. It's also available as a synchronous API for single, non-document, image-only scenarios with performance enhancements that make it easier to implement OCR-assisted user experiences.
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> [!WARNING]
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> The Azure AI Vision legacy [OCR API in v3.2](/rest/api/computervision/recognize-printed-text?view=rest-computervision-v3.2) and [RecognizeText API in v2.1](/rest/api/computervision/recognize-printed-text/recognize-printed-text?view=rest-computervision-v2.1) operations are not recommended for use.
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[!INCLUDE [read-editions](includes/read-editions.md)]
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## How is OCR related to Intelligent Document Processing (IDP)?
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Intelligent Document Processing (IDP) uses OCR as its foundational technology to additionally extract structure, relationships, key-values, entities, and other document-centric insights with an advanced machine-learning based AI service like [Document Intelligence](../../ai-services/document-intelligence/overview.md). Document Intelligence includes a document-optimized version of **Read** as its OCR engine while delegating to other models for higher-end insights. If you are extracting text from scanned and digital documents, use [Document Intelligence Read OCR](../../ai-services/document-intelligence/concept-read.md).
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## How to use OCR
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Try out OCR by using Vision Studio. Then follow one of the links to the Read edition that best meet your requirements.

articles/ai-services/computer-vision/quickstarts-sdk/client-library.md

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ms.devlang: csharp
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# ms.devlang: csharp, golang, java, javascript, python

articles/ai-services/openai/includes/dall-e-dotnet.md

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Use this guide to get started generating images with the Azure OpenAI SDK for C#.
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- An Azure OpenAI resource created in the East US region. For more information, see [Create a resource and deploy a model with Azure OpenAI](../how-to/create-resource.md).
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> [!NOTE]
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> Currently, you must submit an application to access Azure OpenAI Service. To apply for access, complete [this form](https://aka.ms/oai/access). If you need assistance, open an issue on this repo to contact Microsoft.
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> Currently, you must submit an application to access Azure OpenAI Service. To apply for access, complete the form at [https://aka.ms/oai/access](https://aka.ms/oai/access?azure-portal=true). If you need assistance, open an issue on this repo to contact Microsoft.
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## Setup
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[!INCLUDE [get-key-endpoint](get-key-endpoint.md)]
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From the project directory, open the *program.cs* file and replace with the following code:
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From the project directory, open the *program.cs* file and replace the contents with the following code:
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```csharp
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using System;

articles/ai-services/openai/includes/dall-e-go.md

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- An Azure OpenAI resource created in the East US region. For more information, see [Create a resource and deploy a model with Azure OpenAI](../how-to/create-resource.md).
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> [!NOTE]
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> Currently, you must submit an application to access Azure OpenAI Service. To apply for access, complete [this form](https://aka.ms/oai/access). If you need assistance, open an issue on this repo to contact Microsoft.
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> Currently, you must submit an application to access Azure OpenAI Service. To apply for access, complete the form at <a href="https://aka.ms/oai/access" target="_blank">https://aka.ms/oai/access</a>. If you need assistance, open an issue on this repo to contact Microsoft.
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## Setup
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[!INCLUDE [get-key-endpoint](get-key-endpoint.md)]
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articles/ai-services/openai/includes/dall-e-java.md

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- An Azure OpenAI resource created in the East US region. For more information, see [Create a resource and deploy a model with Azure OpenAI](../how-to/create-resource.md).
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> [!NOTE]
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> Currently, you must submit an application to access Azure OpenAI Service. To apply for access, complete [this form](https://aka.ms/oai/access). If you need assistance, open an issue on this repo to contact Microsoft.
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> Currently, you must submit an application to access Azure OpenAI Service. To apply for access, complete the form at [https://aka.ms/oai/access](https://aka.ms/oai/access?azure-portal=true). If you need assistance, open an issue on this repo to contact Microsoft.
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## Setup
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[!INCLUDE [get-key-endpoint](get-key-endpoint.md)]
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articles/ai-services/openai/includes/dall-e-javascript.md

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> Currently, you must submit an application to access Azure OpenAI Service. To apply for access, complete [this form](https://aka.ms/oai/access). If you need assistance, open an issue on this repo to contact Microsoft.
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## Setup
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[!INCLUDE [get-key-endpoint](get-key-endpoint.md)]
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articles/ai-services/openai/includes/dall-e-powershell.md

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[!INCLUDE [get-key-endpoint](get-key-endpoint.md)]
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| Variable | Name | Value |
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| ------------ | ---------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| **Endpoint** | `api_base` | The endpoint value is located under **Keys and Endpoint** for your resource in the Azure portal. Alternatively, you can find the value in **Azure OpenAI Studio** > **Playground** > **Code View**. An example endpoint is: `https://docs-test-001.openai.azure.com/`. |
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| **Key** | `api_key` | The key value is also located under **Keys and Endpoint** for your resource in the Azure portal. Azure generates two keys for your resource. You can use either value. |
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Go to your resource in the Azure portal. On the navigation pane, select **Keys and Endpoint** under **Resource Management**. Copy the **Endpoint** value and an access key value. You can use either the **KEY 1** or **KEY 2** value. Always having two keys allows you to securely rotate and regenerate keys without causing a service disruption.
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:::image type="content" source="../media/quickstarts/endpoint.png" alt-text="Screenshot that shows the Keys and Endpoint page for an Azure OpenAI resource in the Azure portal." lightbox="../media/quickstarts/endpoint.png":::
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# [PowerShell](#tab/powershell)
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[!INCLUDE [environment-variables](environment-variables.md)]
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> [!div class="nextstepaction"]
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> [I ran into an issue with the setup.](https://microsoft.qualtrics.com/jfe/form/SV_0Cl5zkG3CnDjq6O?PLanguage=POWERSHELL&Pillar=AOAI&Product=Chatgpt&Page=quickstart&Section=Set-up)

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